Feature-Based Locomotion Controllers




This paper introduces an approach to control of physics-based characters based on high-level features of movement, such as center-of-mass, angular momentum, and end-effectors. Objective terms are used to control each feature, and are combined by a prioritization algorithm. We show how locomotion can be expressed in terms of a small number of features that control balance and end-effectors. This approach is used to build controllers for human balancing, standing jump, and walking. These controllers provide numerous benefits: human-like qualities such as arm-swing, heel-off, and hip-shoulder counter-rotation emerge automatically during walking; controllers are robust to changes in body parameters; control parameters and goals may be modified at run-time; control parameters apply to intuitive properties such as center-of-mass height; and controllers may be mapped onto entirely new bipeds with different topology and mass distribution, without modifications to the controller itself. No motion capture or off-line optimization process is used.


Martin de Lasa, Igor Mordatch, Aaron Hertzmann, Feature-Based Locomotion Controllers, ACM Transactions on Graphics, 2010, 29, 3, (Proc. SIGGRAPH). BibTex | Errata


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The authors thank David J. Fleet and the reviewers for valuable feedback. This research is supported in part by NSERC, CIFAR, CFI, and Ontario MRI. Part of this work was done while Aaron Hertzmann was on a sabbatical visit at Pixar Animation Studios.